Signature verification is a commonly used biometric authentication method. Compared with other forms of biometric authentication such as fingerprint or iris verification, signature verification has the advantage that it is a historically well-established and well-accepted approbation method and is thus perceived to be less intrusive than modern alternatives. This property makes it particularly attractive to applications in banking, retail and hospitality industries.
Signature verification is divided into two main areas: static (offline) signature verification where signature samples are optically scanned into image representations, and dynamic (online) signature verification where signature samples are collected from a digitizing tablet capable of recording pen movements during writing.
In general, the process of signature verification involves comparing a new signature submitted for testing to a set of previously collected reference signatures to determine whether the new signature is authentic. Having a set of references that captures the natural variation among different authentic signatures of the same subject is crucial for a verification system to operate effectively.
In existing systems, a number of signature samples (typically five to ten) are collected in one enrollment session and used as reference samples. However, there are a number of drawbacks with this scheme.
First, in some applications such as retail, collecting many samples during one enrollment session puts an undue burden on customers. Ideally, the number of signature samples collected during initial enrollment should be limited to no more than three.
Second, even if more samples can be collected during enrollment, samples collected in one session are typically not very representative of the natural variation exhibited by most signers. Often, a larger degree of variation is observed on samples collected from different sessions with long breaks (i.e., days) in between. Furthermore, it is known that samples collected in one session can not capture the “drift” (i.e., a slow shifting of style over a period of time) which is also common among signers.
One known solution to these problems is to first collect the reference samples over several enrollment sessions to capture the current range of variation, then have periodic “re-enrollment” sessions (e.g., once a year) to capture the signature drift. However, this is not very practical because of the extra burden placed on the customers.
Another known solution is to add to the reference set, at a time during or after the regular authentication (e.g., sign-in verification) process, any signature sample that produced a high enough score during verification. However, this policy is not very effective since setting the threshold too high will only allow the addition of samples that are very close to the initial reference samples, thus defeating the purpose of capturing more variation; while setting it too low will increase the risk of adding forgeries, thus polluting the reference set.